stldata

The stlData package contains various data sets representing the City of St. Louis. These data sets are primary designed for teaching statistics, data science, and spatial data analysis using R.

Important Lifecycle Update

As of June 4, 2019, this package has been moved to a “questioning” lifecycle stats - some of its functionality has been shifted to the still-developing gateway package, while other aspects are better handeled by teaching students to import raw data sources. Development has therefore been suspended, with no current plans to return to this package in the future.

Installation

You can install stldata from Github with:

devtools::install_github("slu-openGIS/stlData")

Use with Simple Features

One goal of stldata is to provide accessible data for learning how to manipulate and map simple features objects in R. However, the installation of sf requires a number of dependencies. To make stldata as accessible as possible, sf is not required. If sf is not installed, only the data tables listed below will be fully accessible and functional.

Current Data

Data Tables

The package currently contains eight data tables stored as tibbles with quantitative data about the city:

• stl_tbl_asthma - current asthma prevalence in 2014 by census tract via Centers for Disease Control 500 Cities Project
• stl_tbl_income - 2010 and 2015 median income estimates via the American Community Survey, by census tract
• stl_tbl_insurance - lack of health insurance in 2014 by census tract via Centers for Disease Control 500 Cities Project
• stl_tbl_lead - blood lead level test result data from 2010-2015 via Reuters and 2015 5-year estimates for demographics (poverty and race) via the American Community Survey, by census tract
• stl_tbl_murders - all murders between 2008 and 2016 via the St. Louis Metropolitan Police Department
• stl_tbl_sluPlaces - a small number of locations at Saint Louis University
• stl_tbl_smoking - current smoking in 2014 by census tract via Centers for Disease Control 500 Cities Project
• stl_tbl_water - rivers and streams listed under the Clean Water Act via the Missouri Spatial Data Information Service

Simple Features Objects

The package contains four sf objects describing the City of St. Louis:

• stl_sf_boundary - city boundary
• stl_sf_historic - historic districts
• stl_sf_hydro - Missouri side of the Mississippi River and the River Des Peres
• stl_sf_tracts - 2016 census tracts

Conversion of Tibbles to sf Objects

The following tibbles can be converted to sf objects using the stl_as_sf() function:

• stl_tbl_asthma
• stl_tbl_income
• stl_tbl_insurance
• stl_tbl_lead
• stl_tbl_smoking

Input tables should not be quoted when the stl_as_sf() function is used:

asthma <- stl_as_sf(stl_tbl_asthma)

Useage

Basic Usage

Once the package is loaded, the data contained in stldata can be assigned to data frames in your global environment and then explored. For example, to load the stl_tbl_asthma data:

library("stldata")
asthma <- stl_tbl_asthma
str(asthma)

Additional examples and information are available in each table’s help file. For example:

?stl_tbl_asthma

Skill Building

The stl_tbl_murders and stl_tbl_water data have been created for practicing data wrangling. The murder data can be used for working with demographic data specifically, and the water data have both missing and duplicate information. The stl_tbl_sluPlaces table is meant for introducing basic mapping wither either plot(), ggplot2, or leaflet. All of the tables excepting stl_tbl_sluPlaces contain count or rate data suitable for plotting, and the data measured at the census tract level can be use for practicing joins with demographic data from tidycensus.

Mapping with sf

If you have the development version of ggplot2, the sf objects in the package can be mapped using the geom_sf() function:

ggplot() +
  geom_sf(data = stl_sf_boundary, fill = "#5d5d5d", color = "#5d5d5d") +
  geom_sf(data = stl_sf_historic, fill = "#d48a72", color = "#d48a72") +
  geom_sf(data = stl_sf_hydro, fill = "#72bcd4", color = "#72bcd4")  +
  labs(title = "Historic Districts", subtitle = "St. Louis, MO")

When the tibbles like stl_tbl_asthma are converted to sf objects, they can be mapped as well:

asthma <- stl_as_sf(stl_tbl_asthma)

ggplot() +
  geom_sf(data = asthma, mapping = aes(fill = pctAsthma), color = "#5d5d5d") +
  scale_fill_viridis(name = "Percent") +
  labs(title = "Crude Asthma Prevalence", subtitle = "St. Louis, MO")

Contributor Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.